| |
| """CREMA-D dataset.""" |
|
|
| import os |
| from typing import Union |
|
|
| import datasets |
| import pandas as pd |
|
|
| _DESCRIPTION = """\ |
| CREMA-D is a data set of 7,442 original clips from 91 actors. |
| These clips were from 48 male and 43 female actors between the ages of 20 and 74 |
| coming from a variety of races and ethnicities (African America, Asian, |
| Caucasian, Hispanic, and Unspecified). Actors spoke from a selection of 12 |
| sentences. The sentences were presented using one of six different emotions |
| (Anger, Disgust, Fear, Happy, Neutral, and Sad) and four different emotion |
| levels (Low, Medium, High, and Unspecified). |
| """ |
|
|
| _HOMEPAGE = "https://github.com/CheyneyComputerScience/CREMA-D" |
|
|
| DATA_DIR = {"train": "AudioWAV"} |
|
|
|
|
| class Sample(datasets.GeneratorBasedBuilder): |
| """Crema-D dataset.""" |
|
|
| DEFAULT_WRITER_BATCH_SIZE = 256 |
| BUILDER_CONFIGS = [datasets.BuilderConfig(name="clean", description="Train Set.")] |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| {"file": datasets.Value("string"), "label": datasets.Value("string")} |
| ), |
| supervised_keys=("file", "label"), |
| homepage=_HOMEPAGE, |
| ) |
|
|
| def _split_generators( |
| self, dl_manager: datasets.utils.download_manager.DownloadManager |
| ): |
| data_dir = dl_manager.extract(self.config.data_dir) |
| if self.config.name == "clean": |
| train_splits = [ |
| datasets.SplitGenerator( |
| name="train", gen_kwargs={"files": data_dir, "name": "train"} |
| ) |
| ] |
|
|
| return train_splits |
|
|
| def _generate_examples(self, files: Union[str, os.PathLike], name: str): |
| """Generate examples from a Crema unzipped directory.""" |
| key = 0 |
| examples = list() |
|
|
| audio_dir = os.path.join(files, DATA_DIR[name]) |
|
|
| if not os.path.exists(audio_dir): |
| raise FileNotFoundError |
| else: |
| for file in os.listdir(audio_dir): |
| res = dict() |
| res["file"] = "{}".format(os.path.join(audio_dir, file)) |
| res["label"] = file.split("_")[-2] |
| examples.append(res) |
|
|
| for example in examples: |
| yield key, {**example} |
| key += 1 |
| examples = [] |
|
|
